Postdoc Fellow, Ph.D., B.Sc.

Xintong Li obtained her Bachelor of Science Degree in Remote Sensing Science and Technology from China University of Geosciences (Wuhan), Hubei, China in 2016. She received her Ph.D. in Environmental Science from Shandong University, Shandong, China in 2023. She is currently a postdoctoral researcher supervised by Dr. Shuguang Wang in Shandong University, Shandong, China and Dr. Bin Chen in NRPOP Lab, Memorial University of Newfoundland, NL, Canada.

 

Her research interest is using explainable AI aided hydrological and water quality modeling in the environmental field to address risks under changing environments.

 

Academic Achievement Content

Selected Publication

1. Li, X., Zhang, X., & Wang, S. (2022). A hybrid statistical downscaling framework based on nonstationary time series decomposition and machine learning.Earth and Space Science, 9(6), e2022EA002221. https://doi.org/10.1029/2022EA002221
2. Li, X., Zhang, X., & Wang, S. (2021). Managing conflicts and equitability in hierarchical decision making for water resources planning under fuzzy uncertainty: A case study of Yellow River, China.Journal of Hydrology: Regional Studies, 38, 100963. https://doi.org/10.1016/j.ejor.2020.09.048
3. Li, X., & Zhang, X. (2019). Predicting ground-level PM_2.5concentrations in the Beijing-Tianjin-Hebei region: A hybrid remote sensing and machine learning approach. Environmental Pollution, 249, 735-749. https://doi.org/10.1016/j.envpol.2019.03.089
4. Wang, L., Huang, L., Xia, H., Li, H., Li, X., & Liu, X. (2019). Application of a multi-electrode system with polyaniline auxiliary electrodes for electrokinetic remediation of chromium-contaminated soil. Separation and Purification Technology, 224, 106-112. https://doi.org/10.1016/j.seppur.2019.04.027

Conference

1. Statistical Downscaling of Temperature and Precipitation of California Using A NonStationary Time Series Decomposition and Machine Learning, Oral Presentation, AGU Fall Meeting 2019
2. Predicting Ground-Level PM_2.5in the Beijing-Tianjin-Hebei Region Using Satellite and Machine Learning,Poster Presentation, AGU JINT MEETING 2018